An iterative MMSE procedure for parameter estimation of damped sinusoidal signals

We propose an iterative minimum mean square error (MMSE) approach to parameter estimation of multiple exponentially damped sinusoids embedded in white Gaussian noise. The approach splits the observed signal into its constituent components and proceeds to estimate the parameters of the highest energy signal component first, followed by the next highest energy signal component, and so on. This scheme reduces the computational complexity of the overall procedure by approximating the multidimensional integrals with several two-dimensional integrals. For the evaluation of these integrals, we introduce an adaptive Gaussian procedure. We present computer simulation results that show the performance of our approach and compare it with the performance of the alternating projection and the expectation-maximization schemes.